LLM watermarking embeds subtle, detectable signals in AI-generated text to identify its origin, addressing misuse concerns like impersonation, ghostwriting, and fake news. Despite its promise to distinguish humans from AI text and prevent misinformation, the field faces challenges. The numerous and complex watermarking algorithms, alongside varied evaluation methods, make it difficult for researchers and the… →

The expansion of question-answering (QA) systems driven by artificial intelligence (AI) results from the increasing demand for financial data analysis and management. In addition to bettering customer service, these technologies aid in risk management and provide individualized stock suggestions. Accurate and useful replies to financial data necessitate a thorough understanding of the financial domain because… →

By utilizing language thinking, Large Vision-Language Models (VLMs) have demonstrated remarkable capabilities as adaptable agents that can solve a wide range of tasks. A good way to improve VLM performance is to fine-tune them with specific visual instruction-following data. Their performance is greatly enhanced by this strategy, which teaches them to obey precise visual directions. … →

Artificial intelligence email assistants have made writing an email quicker and easier. Automatic task completion, message prioritization, and prompt, insightful answers are just how AI email assistants may ease the burden of managing your inbox. As a result, users can direct their attention to the most pressing emails and get more done in less time.… →

Generative AI (Gen AI), capable of producing robust content based on input, is poised to impact various sectors like science, economy, education, and the environment. Extensive socio-technical research aims to understand the broad implications, acknowledging risks and opportunities. A debate surrounds the openness of Gen AI models, with some advocating for open release to benefit… →